Protected Connected Land (ProtConn)

Source: vignettes/ProtConn.Rmd 
library(Makurhini)
library(raster)

Overview

We will explore the ProtConn indicator which was developed to report international conservation targets (Saura et al. 2017), the indicator offers you an analysis of protected areas connectivity for a particular region.

Loading data (two ecoregions and one set of protected areas, both shapefiles):

#Protected areas
data("Protected_areas", package = "Makurhini")

#Ecoregions
data("regions", package = "Makurhini")

ProtConn estimation for a single ecoregion

In the following example, we will estimate the ProtConn indicator and fractions in one ecoregion using two dispersal distances (10 and 30 km) and a connection probability of 0.5. Also, we will use a Transboundary buffer of 50 km (50000 meters), the distance between protected areas will be using centroids.

region <- regions[1,]
test.1 <- MK_ProtConn(nodes = Protected_areas, region = region,
                    attribute = "Intersected area", area_unit = "ha",
                    distance = list(type= "centroid"),
                    distance_thresholds = c(10000, 30000),
                    probability = 0.5, transboundary = 50000,
                    LA = NULL, plot = TRUE, dPC = FALSE,
                    write = NULL, SAGA = FALSE, intern = FALSE)

Exploring the results for a single ecoregion

  • Result 10 km:
test.1$d10000$`Protected Connected (Viewer Panel)`
Index Value ProtConn indicator Percentage
EC(PC) 130189.18 Unprotected 92.540
PC 1.2324e-03 Prot 7.460
ProtConn 3.511
ProtUnconn 3.950
RelConn 47.058
ProtConn_design 3.950
ProtConn_Bound 3.511
ProtConn_Prot 97.512
ProtConn_Trans 0.000
ProtConn_Unprot 2.488
ProtConn_Within 94.784
ProtConn_Contig 2.728
ProtConn_Within_land 3.327
ProtConn_Contig_land 0.096
ProtConn_Unprot_land 0.087
ProtConn_Trans_land 0.000 
test.1$d10000
#> $`Protected Connected (Viewer Panel)`
#> 
#> $`ProtConn Plot`

  • Result 30 km:
test.1$d30000$`Protected Connected (Viewer Panel)`
Index Value ProtConn indicator Percentage
EC(PC) 149504.72 Unprotected 92.540
PC 1.6252e-03 Prot 7.460
ProtConn 4.031
ProtUnconn 3.429
RelConn 54.040
ProtConn_design 3.429
ProtConn_Bound 4.031
ProtConn_Prot 84.914
ProtConn_Trans 0.000
ProtConn_Unprot 15.086
ProtConn_Within 82.538
ProtConn_Contig 2.376
ProtConn_Within_land 3.327
ProtConn_Contig_land 0.096
ProtConn_Unprot_land 0.608
ProtConn_Trans_land 0.000 
test.1$d30000
#> $`Protected Connected (Viewer Panel)`
#> 
#> $`ProtConn Plot`

ProtConn estimation for two or more ecoregions.

Now, we will use the three ecoregions. The processing time will be longer when using more regions, although we can reduce it using the parallel argument.

test.2 <- MK_ProtConnMult(nodes = Protected_areas, regions = regions,
                          attribute = "Intersected area", area_unit = "ha",
                          distance = list(type= "centroid"),
                          distance_thresholds = c(10000, 30000),
                          probability = 0.5, transboundary = 50000,
                          plot = FALSE, write = NULL, parallel = TRUE,
                          intern = FALSE)

Exploring some results

  • Table summary result:
names(test.2)
#> [1] "ProtConn_10000" "ProtConn_30000"
test.2$ProtConn_10000$ProtConn_overall10000
ProtConn indicator Values(%) SD SEM normal.lower normal.upper basic.lower basic.upper percent.lower percent.upper bca.lower bca.upper
3 Unprotected 94.913 2.472 1.427 92.745 97.299 92.351 97.285 92.540 97.474 92.540 96.557
4 Prot 5.087 2.472 1.427 2.701 7.255 2.715 7.649 2.526 7.460 2.526 6.732
5 ProtConn 2.388 1.326 0.766 1.117 3.553 1.264 3.850 0.925 3.511 0.925 2.988
6 ProtUnconn 2.700 1.182 0.682 1.551 3.735 1.450 3.799 1.601 3.950 1.601 3.483
7 RelConn 45.124 7.709 4.451 37.972 52.056 38.566 53.616 36.632 51.682 36.632 50.141
8 ProtConn_design 2.700 1.182 0.682 1.551 3.735 1.450 3.799 1.601 3.950 1.601 3.483
9 ProtConn_Bound 2.388 1.326 0.766 1.117 3.553 1.264 3.850 0.925 3.511 0.925 2.988
10 ProtConn_Prot 97.767 1.706 0.985 96.209 99.335 95.947 99.331 96.202 99.586 96.202 98.895
11 ProtConn_Trans 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
12 ProtConn_Unprot 2.233 1.706 0.985 0.665 3.791 0.669 4.053 0.414 3.798 0.414 3.361
13 ProtConn_Within 95.261 1.985 1.146 93.455 97.096 93.081 96.964 93.558 97.441 93.558 96.555
14 ProtConn_Contig 2.506 0.315 0.182 2.205 2.788 2.283 2.866 2.145 2.728 2.145 2.700
15 ProtConn_Within_land 2.283 1.272 0.735 1.067 3.402 1.240 3.701 0.866 3.327 0.866 2.880
16 ProtConn_Contig_land 0.059 0.036 0.021 0.024 0.091 0.023 0.095 0.024 0.096 0.024 0.083
17 ProtConn_Unprot_land 0.044 0.039 0.022 0.006 0.079 0.002 0.078 0.011 0.087 0.011 0.070
18 ProtConn_Trans_land 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
  • Shapefile result:
test.2$ProtConn_10000$ProtConn_10000
#> Simple feature collection with 3 features and 19 fields
#> geometry type:  MULTIPOLYGON
#> dimension:      XY
#> bbox:           xmin: 2287307 ymin: 792114.5 xmax: 3085667 ymax: 1392441
#> CRS:            +proj=lcc +lat_1=17.5 +lat_2=29.5 +lat_0=12 +lon_0=-102 +x_0=2500000 +y_0=0 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
#>   OBJECTID    EC(PC)         PC Unprotected  Prot ProtConn ProtUnconn
#> 1       61 130189.18 1.2324e-03      92.540 7.460    3.511      3.950
#> 2      143  54276.11 8.5645e-05      97.474 2.526    0.925      1.601
#> 3      772 186165.71 7.4341e-04      94.724 5.276    2.727      2.549
#>   RelConn ProtConn_design ProtConn_Bound ProtConn_Prot ProtConn_Trans
#> 1  47.058           3.950          3.511        97.512              0
#> 2  36.632           1.601          0.925        96.202              0
#> 3  51.682           2.549          2.727        99.586              0
#>   ProtConn_Unprot ProtConn_Within ProtConn_Contig ProtConn_Within_land
#> 1           2.488          94.784           2.728                3.327
#> 2           3.798          93.558           2.644                0.866
#> 3           0.414          97.441           2.145                2.657
#>   ProtConn_Contig_land ProtConn_Unprot_land ProtConn_Trans_land
#> 1                0.096                0.087                   0
#> 2                0.024                0.035                   0
#> 3                0.058                0.011                   0
#>                         geometry
#> 1 MULTIPOLYGON (((2553705 100...
#> 2 MULTIPOLYGON (((2745325 859...
#> 3 MULTIPOLYGON (((2973030 103...
ProtConn <- test.2[[1]]$ProtConn_10000
mapview(ProtConn, zcol = c("ProtConn"), col.regions =c("#91CF60", "#FC8D59", "#FFFFBF"))
  • It is important not to forget that you can change the type of distance using the distance (see, distancefile() ) argument:

Euclidean distances: * distance = list(type= “centroid”) * distance = list(type= “edge”)

Least cost distances: * distance = list(type= “least-cost”, resistance = “resistance raster”) * distance = list(type= “commute-time”, resistance = “resistance raster”)

Reference:

  • Saura, S., Bastin, L., Battistella, L., Mandrici, A., & Dubois, G. (2017). Protected areas in the world’s ecoregions: How well connected are they? Ecological Indicators, 76, 144–158.